jenniferhooley

Huh? I have a 650sqft house, it costs 430K in a small town. I looked at building a new place, it would cost roughly the same to hire a building team to make it - not to mention years of waiting on development. The land is fairly affordable if I buy a little bit out of town. It's the cost of building that is stopping me.

Or we just wait for automation and robotics to make building housing much cheaper and the free market system to fix things - which 5 years ago I assumed was too far out, but with all the advances in the sector, seems like we might get significantly cheaper building costs within the next 10 years or so.

Here I will quote what I said to you - it's super explicit and obvious I'm asking how one would find it useful.

"How is it useful? I'm no expert in combustion engines, so I'd hesitate to rely on a slop graphic like this to learn about them as I doubt the creator has any idea about them either."

Notice I say "How is it useful?" and "I'd hesitate to rely on a slop graphic like this to learn".

I think I'm being very obvious about the fact that I can't understand how one would find it "useful" to "learn". Absolutely NOWHERE did I say you can't be entertained by it.

Where did I say what people are allowed to find entertaining? It would be insane to tell someone what they should find entertaining, that's the dumbest thing I've ever heard.

As for useful, I'm genuinely trying to understand HOW you find something useful that may or may not have zero accuracy to the thing in which it's portending to showcase?

When I don't know about something - I would find someone who's really knowledgeable (or a resource that's vetted), and learn from that obviously. I don't want to learn something completely unverified and made up? That makes no logical sense.

Just like my friend's slop graphics. I imagine learning geometry from that and fundamentally locking in incorrect knowledge when there are many thousands of resources that would teach me correctly - this makes no sense right? Would you prefer to learn from the pretty graphics that are teaching you nothing?

How is it useful? I'm no expert in combustion engines, so I'd hesitate to rely on a slop graphic like this to learn about them as I doubt the creator has any idea about them either.

It's like a friend - he was like "Look at this awesome set of categorized interactive animations from claude to learn geometry!".

And like 60% of the animations were technically just wrong. Very pretty though, and the effects were cute... I guess...?

Oh, you think we are going to have another breakthrough in artificial intelligence rivaling the one we had in 2022 this year or next? What research or studies lead you to believe this? Could I see one?

I haven't personally seen the research leading me to believe there's a massive new intelligence breakthrough on the horizon but maybe I missed it!

As to the current version - I use AI constantly, as in 12 hours a day 7 days a week specifically for high-end game development. It is currently so far from the 2027 prediction that it's hilarious if you think a little incremental improvement (e.g., like from opus 4.6 to Fable) is going to bring us there.

No. Anyone who doesn't code with AI - while retaining a deep knowledge and understanding of the problem domain - is falling behind.

I hate to say this tbh, I loved hand-writing code. I made a great living for 20 years, and I absolutely loved it and was quite good at it.

Hand-typing code is just slower now; there’s no two-ways about it. You are either going to be slow and a bad hire for businesses, or you figure out how to adopt AI into your workflow to speed up.

One thing I think people don't realize is that deep knowledge of programming, performance, architectural, and domain specific trade-offs makes a skilled engineer about 1000X faster than someone without those skills -with AI. But yes, now unskilled people can actually make apps/software. They just tend to be slow, and their products are full of bugs, security flaws, and abysmal performance.

So we went from: Skills = can or cannot ship any software at all. Now we are at: Skills = can ship better software much faster than unskilled people.

I was actually faced with this recently. I decided to learn Rust and port one of my side projects to it. Initially, I moved extremely slowly, and the AI made truly horrific architectural decisions because I didn't have the knowledge of how to direct it, especially compared to my primary languages.

However, once I gained a firm grasp of Rust, I was better able to properly direct the AI to fix fundamental issues and architect things properly. My speed increase multiplier proved to be directly proportional to my growing knowledge of both the language and the domain.

Skill and knowledge combined with AI, when used appropriately, absolutely multiply your speed and quality. I really think once you understand what AI can do, and how to utilize it to produce better code, faster than before, there truly is no going back.

I'm finding a path forward that I actually enjoy now and don't really see losing my value (no telling how things will change in the future), I can have more time to focus on really quality/solid/performant and useful systems with less time just typing one character out at a time.

You could have talked to me 3 months ago and I'd never imagine I'd say the above btw. I REALLY enjoyed code writing and earlier AI models without harnesses were pretty useless for anyone skilled at development. Now with stuff like deepseek Flash I feel like I have a happy medium of 100% directed/fast code turnaround, less typing, more deep focus on architecture, systems, and the actual end product.

Programmers can use smaller models like deepseek v4 flash for 98% of the same productivity as SOTA models and cost (true cost) around $10-$30 a month. So I doubt most people who heavily use them are too concerned. It's only vibe/hobby coders who really need SOTA and they probably don't think about it much.

Man the one-shot game that is genuinely good in 2027 is crazy. A good game typically takes around 3-8 years of development by multiple skilled people. Maybe 3 years or so for 1 guy that's super dedicated.

Right now single prompt with Fable can get us a small protype of like 1 game mechanic that's not even remotely production ready. So this guy thinks it'll 100,000X in a year.

AI boosters are something else.

Let's say we're prototyping an interactive tree (this is totally made up, but you get the idea):

Take this data input and convert it to a Sugiyama-style tree with hand-drawn feeling lines connecting the nodes. We need the ability to activate a random subset of nodes with a paint splash. The whole thing should feel organic, incorporating small motion effects. As the nodes are activated, the edges should look like a hand-drawn painting effect drawing toward the node, and then SPLASH onto the end node as it changes from black to deep red. The background should utilize a muted paper color, and we must adhere to this color palette for all elements (PALETTE).

...then back-and-forth 10 prompts or so to get the prototype I was looking for. Comparing these types of things between Fable and Opus, something like this would be quite a bit less glitchy, prettier, and closer to the quick prototyping I needed than what I got with Opus 4.8.

Now, when I went deep into a complex codebase to fix a small issue or optimization that spanned many files and was fairly unique from anything in the training data, I didn't really see any noticeable difference between Fable and Opus 4.8.

I felt like it was about 10X better at "pretty" but straightforward 1 shot'ish type tasks. Not so different for complex and specific tasks in real code-bases.

Why do you say it was a lot better, what type of tasks were you testing it on?

Yes, but the AI will handle asking you everything. Here's how easy it is to make a game that functions like his but without the polish - put Claude in plan mode 1 prompt, then answer any questions it has:

--- Make me a threejs game in html. The "game" is where you can tap a button to add a log to a cutting block. You have an axelike (e.g., a stem cube for handle and slim cube for axe blade) object that you can axe into the wood, and wherever the head intersects the underlying "log" cylinder it splits the log.

So blade is a hittest object, where that object hits the spawned log, the log splits, use a decent physics lib (ammoJS is fine) so it feels good. Do you have any questions? ---

After answering about 5 basic questions, the above made a cute little physics based log cutting game very similar to this guy's demo - now it'd probably take about 5-8 more hours to slowly prompt out a more polished version. This stuff is really easy - you don't have to have any experience in game dev to prompt it up.

You mean by "we illustrate and print it", we have an AI illustrate it?

How much of the code do you think is written by AI? Just curious as I do video game development and just recently started heavily using opencode agentic development with the Flash models (instead of essentially using zero AI assistance before). I actually really like the workflow and find it helps speed things up a hair and in general allow faster testing/tooling builds/etc. which are super helpful to make a game feel really good.

Kind of curious how other people are using agentic code tools for game dev!

I thought this might be interesting - but I'm on PC and there are no quick ways to pop on that site and see the app in action. Like no screenshots or anything? So I left and likely will never be back. Always good to have some quick screenshots/gifs of apps in action or people bounce on your landing/sales page never to be seen again.

I do a lot of game stuff (professionally and just for fun) and play around with maxing out vibeing little feature samples.

This would be fairly straightforward vibecode over a day or two.

Definitely not to throw shade at the guy. But yea, there is nothing here that wouldn't be easily vibeable.

Yeah, I feel like nobody realizes you can put together premade/open source game base + assets in a weekend. And before LLMs there were guys who specialized in this and got really popular on social media for "making a game in a weekend".

Always interesting reading threads about topics you know deeply and everyone else has no familiarity or understanding about what they are seeing. Stark reminder of how easy it is to be impressed when you don't understand a topic.

I feel like you don't have any friends who make software but don't know how to code.

Yes, they do make software now - whereas it was impossible before. You may be absolutely shocked at how bad LLM code can be when prompted from a noncoder. How buggy, and how absolutely rife with security problems it can have. I honestly don't know how they can get LLMs to write such bad software - but somehow they can. This is from people who have been vibe coding for 3 years straight btw (huge amount of time p/day).

You mean theoretically in the future? Or right now?

Vocal minority? Perhaps the majority are just getting fed up with vibe coded mediocre stuff that's significantly worse in every single way to other real options out there?

"I thought we were beyond this by 2026."

Have you been asleep for the last 4–8 years? We aren't even 'beyond this' compared to where we were 15 years ago. In case you haven't noticed, the US has been going backward for years: Americans fundamentally don't give a shit about anything except maximizing GDP, regardless of cost - and in fact, some sectors thrive on that externalized 'cost.' I've noticed your sentiment a few times on HN lately and I'm befuddled every time, like what in your life makes you think we are beyond this kind of thing?

Just depends what you are working on. If you are trying to make a video game that's at a level of a decent indie game (think Hades/Baazar/etc), making UI elements/VFX/complex shaders/etc that are organic/interactive/animated that don't feel like a little dogshit vibeslop web-game, then none of the models are even close to good enough to get it done easily. Huge percentage of problems in top 3% games is really hard for any of the models to do with simple prompting.

Personally I don't really care, because I like coding and learning myself and DeepSeek Flash is all I really care about. But it's really easy to have a ton of benchmarks where the top models can't get anywhere close - and I like to test them on these problems to see how good they are getting.

Fable 5 is def a little better than 4.8 btw.

"I want freedom to do what i want and not sitting in front of a computer and coding for some company."

"Please AI lets burn down knowledge work and labor work"

"Let people do old handcraft jobs."

So many presuppositions about what people want to do.

As a child I spent a lot of time programming and doing "knowledge work" because it's fun - I don't enjoy "old hand-crafted jobs". Sure, let's definitely destroy capitalism in it's current state I suppose. But I find people like you who hate knowledge-work/coding and think everyone else must feel the same and only do it for the money a bit out-of-touch.

This is always a worry, but typically, being first to market is the most important part. As long as you can scale quickly and maintain your edge, this doesn't seem like such a big deal.

However, my product is so far removed from anything these companies would make, on top of that I'm using open-source models (e.g., oss gpt 120b is really, really good). I don't use any of the main providers like AWS, etc., and the underlying AI systems are only about 5% of the product. I need it for the idea to work, but it is a tiny part of the full offering. I can't really imagine it would make any sense for Amazon, etc., to compete on something like this.

But yes, in the end, huge conglomerates with infinite money can destroy smaller entrepreneurs - but that's not really any different than it's been for decades pre-AI.

I think that most people are pretty short-sighted about the utility cases right now (which is understandable given the negative feelings about a lot of what's currently going on).

There are a lot of really useful things that were impossible before. But none of these use cases are "easy," and they all take years of engineering to implement. So, all we see right now are trashy, vibe-code style "startups" rather than the actual useful stuff that will come over the years from experienced architects and engineers who can properly utilize this technology to build real products.

I'm someone who feels very frustrated with most of the chatter around AI - especially the CEOs desperate to devalue human labor and replace it - but I am personally building something utilizing AI that would have been impossible without it. But yeah, it's no walk in the park, and I've been working on it for three years and will likely be working on it for another year before it's remotely ready for the public.

When I started, the inference was too slow, the costs were too high, and the thinking-power was too poor to actually pull it off. I just hypothesized that it would all be ready by the time I launch the product. Which it finally is, as of a few months ago.

Link me the research on the hard engineering tasks they've done on database kernels, I'd love to see it, sounds interesting.

As long as people comment, "Only bad/stupid engineers hand-write code because LLMs are better in every way," and that's objectively not true in various engineering circles, I'll keep trolling them and being just as hyperbolic in the inverse because it amuses me. Don't take things too seriously on the internet; you'll have a bad time ;)

Yeah, I agree with you. My experience has been very similar, when the actual game logic gets complex, BT's become a bit of a maintenance nightmare, making it super hard to reason about the system flow.

I ultimately landed on a flag-driven, hierarchical state machine. Instead of implementing a full tree traversal, which requires complex flow control nodes, I use bit flags to define my system's entire set of rulesets or invariants.

A state doesn't need to ask "what do I do next?" but rather "are my activation conditions met?" These conditions are defined as bitwise flags evaluated through standard bit-masking operations (AND, OR, XOR, etc.). For example, a state might only become active if flags IN_RANGE & GOAL_IS_NPC & PATH_BLOCKED. The flags allow me to mathematically encode complex prerequisite combinations as simple integer comparisons.

I found this approach makes the transition logic nice and clean. It shifts the burden from managing the flow (which is complex) to managing the data state (which is simple and deterministic). The system still feels like a full BT - it has hierarchy and sequential logic - but the decision process is purely data-driven, which makes it really easy to reason about even when there's a many of layers of complexity for each state/substate.

You are in a bubble. Some segments use essentially no AI, while others have gone all in. Just because the type of engineers you're surrounded by do engineering that is obsolete doesn't mean that's the case across the board. All the best game engineers I know still write at least 90% of the code (probably closer to 99%). The bad ones use AI nearly exclusively - just like yourself. They can't create very complex or performant game systems, and they struggle even with highly unique or interactive game UI systems. I've looked over their code; almost every choice is bad, and it's clear why their projects completely collapse after a certain point. They simply can't build super complex, performant, or novel systems.

I'm going to assume you do the type of engineering where all the hard problems are solved for you already, and you are merely connecting inputs/outputs and hooking up APIs. Because, frankly, the value in "software plumbing" is gone; anyone with a Claude license can do that now.